Analysis of a QTL involved in resistance to Viral Hemorrhagic Septicemia (VHS) virus in Rainbow trout: from QTL detection to gene expression

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Analysis of a QTL involved in resistance to Viral Hemorrhagic Septicemia (VHS) virus in Rainbow trout:

from QTL detection to gene expression

Carine Genet

To cite this version:

Carine Genet. Analysis of a QTL involved in resistance to Viral Hemorrhagic Septicemia (VHS) virus in Rainbow trout: from QTL detection to gene expression. Master. AQUAEXCEL Training Course (Contribution of genomic approaches to the development of a sustainable aquaculture for temperate and Mediterranean fish), 2013, 28 diapos. �hal-02804635�

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Analysis of a QTL involved in resistance

to VHS virus in rainbow trout : From QTL

detection to Gene expression

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Caused by a rhabdovirus virus genome size 12 kb

Single-stranded RNA genome with 5 structural proteins

Ubiquitous disease (> 65 fish species affected) Disease symptoms :

hemorrhage

Viral Hemorrhagic Scepticaemia

Viral Hemorrhagic Scepticaemia ::

hemorrhage exophthalmia necrosis

CNS disorders.

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QTL

QTL detection

detection

Phenotype - divergent trait

Genotype

~150 microsatellite markers (whole genome scan)

Use of statistical tests

LINK between allele from genetic

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Phenotype

VREFT

waterborne infection

survival, death to VHSV.

Viral Replication in Excised Fin Tissues (VREFT).

+ VHSV

Low VREFT High VREFT

Quillet et al., 2001 Dis Aquat Org Quillet et al.,2007 Dis Aquat Org

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R

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3 generations of 2 reference

3 generations of 2 reference pedigree families

pedigree families

F0 F1

RR

QQ

X

SS

qq

R

S

Qq

VREFT =0.7 VREFT =52

RR

QQ

X

SS

qq

VREFT =8 VREFT =200

R

S

Qq

RR

QQ

Qq

Gynogenesis F2

_RR

qq

SS

QQ

SS

qq

Qq

Waterborne infection n=1,125 n=1,200 VREFT values n=158 n=300

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Principle of QTL detection

M

m

Q

q

F1 heterozygote

Fish number Distribution of progeny performance according to marker allele Fish number Performance marker allele survival death

QTL effect

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In practice

10 15 20 25 30

F

ré

q

u

e

n

c

y

allele from R grand-parent allele from S grand- parent 0 5 10

F

ré

q

u

e

n

c

y

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7 QTLs detected on 6 differents chromosomes. One major QTL

This QTL explained 33% to 49% of the VREFT phenotypic variance

Genome wide threshold for significant QTL

OMY 3

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Fine mapping of the major QTL

Objective = identification of causal gene

Linkage map (4 microsatellites, 3 SNPs) Physical map (2 contigs)

4 full-sequenced BACs

PAGE Truite (Y. Guiguen, C. Genêt, P. Boudinot)

Ots526NWSC** 0,0 Omy1060/2INRA** 1,7 Omy1426/2INRA** 4,3 OMM1778/2 OMM5000/2* 6,9 OmyS_0001-2 10,3 OmyRGT13/2TUF* OMM1138* 12,0 Omi175/2UF 16,0 Omy272/2UoG 21,4 Str4/2INRA OmyUW1077** 23,1 One102Omy1300/2INRA** 24,0 Omy1308INRA 33,1 Omy1009INRA* Omy1067INRA* 107,4 Omy1136INRA* 113,0 Omy1241INRA** OMM5005 118,7 OMM1599 Omy1392INRA Sc321* OmyS_0172 OmyS_0471* 119,5 835B11 125H06 Ctg 5493 483H06 Ctg 3254 425H10 Omy1308INRA 33,1 Omy1323/2INRA 34,0 Omy1006UW** 42,0 CI_B191**Omy1373INRA 43,2 OMM1765 45,9 Omy1027INRA 46,8 OMM1058 53,2 OMM1083 54,1 C BHMS129** 76,0 OMM5146** 77,8 Omy1349INRA* 86,7 OMM5164 88,4 OmyS_0399* 90,3 OMM1053* 97,9 Omy1009INRA* 107,4 Omy1136INRA* 113,0 Omy1241INRA** OMM5005 118,7 OMM1599 Omy1392INRA Sc321*OmyS_0172 OmyS_0471* 119,5

QTL

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Not a contiguous region (still some gaps in the QTL region)

many (too much ?) candidate genes

Interferon receptor = critical for innate and adaptative immunity against viral infection

Trim family proteins : involved in pathogen-recognition

CRFBs : cytokine receptors family member B. Interferon receptor activity TLR 7- 8 : toll like receptors : recognition of viral ssRNA.

C1 q like protein: complement components : role in mediating and modulating C1 q like protein: complement components : role in mediating and modulating the immune response

So what ?

Creation of additional recombination (long lasting) Use of gene expression data

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BC1

A B C D E a b c d e A B C D e a b c d e A B c d e a b c d e A b c d e a b c d e a b c d e a b c d e A B C d e a b c d e A B C d e a b c d e A B C D E a b c d e

Q

q

a b c d e a b c d e

q

MeishanLarge White

Additional recombination

BC2

q q

Q

q

Q

q

Q

q

E e e e e e e e e e e e e e

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A B C d e a b c d e A B C d e a b c d e A B C D E a b c d e

Q

q

a b c d e a b c d e

q

MeishanLarge White

Additional recombination

q q

Q

q

e e e e

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Gene expression data

Transcriptome analysis between resistant or sensitive clones.

spleen fin spleen fin

Control

spleen fin spleen fin

Control Infected

Spleen: major lymphoid organ (6 days after waterborne infection)

Fin bases: virus entry site (24 h after waterborne infection) Three biological replicates

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Illumina

Illumina library

library sequencing

sequencing

SAMPLE Flowcell lane Number of Reads Total

NAS 0.75 189 831 614

RNA cDNA library high throughput sequencing

NAS 0.75 189 831 614 NBS 0.75 273 541 146 NAI 1.5 542 868 472 NBI 1.5 477 336 156 RAS 0.75 283 557 922 RBS 0.75 278 650 541 RAI 1.5 573 768 954 RBI 1.5 499 817 886 1 483 577 388 1 635 795 303

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Bioinformatic

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Statistical

Statistical analyses

analyses

Principal component analysis

Viewing of sample consistency

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Statistical

Statistical analyses (R 3.0.1)

analyses (R 3.0.1)

HTSFilter

Package (Rau et al.,2013)

Compute a similarity index between biological replicates Identify a filtering threshold

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Statistical

Statistical analyses (R 3.0.1)

analyses (R 3.0.1)

Package DESeq2

(Love and al. 2013)

Test for differential expression by use of negative binomial generalized linear models.

Benjamini-Hochberg multiple testing adjustment procedure.

Spleen

Fin

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Identification of differentially expressed genes

condition Pvalue<0.01 log2FC |0.8| unknow

Spleen IC 51.600 2.272 1.384

Spleen IC 5.273 1.425 821

FIC 2.133 223 112

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Next steps

steps

Perform networks and gene pathways analysis

Web-based application for analyzing and interpreting the « biological meaning » of transcriptomic data

Database of high-quality information obtained from research articles Database of high-quality information obtained from research articles (human) manually curated by PhD scientists .

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Next steps

Cross-check these data with positional ones.

Do we have differentially expressed genes among our positional candidate genes ?

Functional candidate genes positional candidate genes ? (exploit comparative mapping data)

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Whole genome sequencing of DH clones

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Quantitative PCR validation

Selection of 100 genes

A method that allows to follow in real time the amplification of a target gene.

Time course analysis of selected DE genes during VHSV

infection

0 3 6 9 12 24 hpi 200₀ 400 600 800 1000 1 2 3 4 5 6 0 200 400 600 800 1000 1200 1400 1 2 3 4 5 6

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Conclusion

Highlight DE genes involved in virus resistance

Characterize the corresponding networks/ pathways involved

Detailed early Kinetics of virus infection in fin and spleen

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D.Esquerré C. Klopp M. Bernard C. Genet E. Quillet C. Ciobotaru N. Dechamp F. Krieg E. Verrier D. Laloé IERP Jouy en josas S. Derozier D.Esquerré Financements :AAP GA P. Boudinot A. Louis H. Roest Crollius Y. Guiguen

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